Vertical structure of biomass burning aerosol transported over the southeast Atlantic Ocean

Biomass burning in southwestern Africa produces smoke plumes that are transported over the Atlantic Ocean and overlie vast regions of stratocumulus clouds. This aerosol layer contributes to direct and indirect radiative forcing of the atmosphere in this region, particularly during the months of August, September and October. There was a multi-year international campaign to study this aerosol and its interactions with clouds. Here we report on the evolution of aerosol distributions and properties as measured by the airborne high spectral resolution lidar (HSRL) during the ORACLES (Observations of Aerosols above Clouds and their intEractionS) campaign in September 2016. The NASA Langley HSRL-2 instrument was flown on the NASA ER-2 aircraft for several days in September 2016. Data were aggregated at two pairs of 2° × 2° grid boxes to examine the evolution of the vertical profile of aerosol properties during transport over the ocean. Results showed that the structure of the profile of aerosol extinction and microphysical properties is maintained over a one to two-day time scale. The fraction of aerosol in the fine mode between 50 and 500 nm remained above 0.95 and the effective radius of this fine mode was 0.16 μm from 3 to 5 km in altitude. This indicates that there is essentially no scavenging or dry deposition at these altitudes. Moreover, there is very little day to day variation in these properties, such that time sampling as happens in such campaigns, may be representative of longer periods such as monthly means. Below 3 km there is considerable mixing with larger aerosol, most likely continental source near land. Furthermore, these measurements indicated that there was a distinct gap between the bottom of the aerosol layer and cloud tops at the selected locations as evidenced by a layer of several hundred meters that contained relatively low aerosol extinction values above the clouds.

Midlatitude mixed-phase stratocumulus clouds and their interactions with aerosols: how ice processes affect microphysical, dynamic, and thermodynamic development in those clouds and interactions?

Midlatitude mixed-phase stratocumulus clouds and their interactions with aerosols remain poorly understood. This study examines the roles of ice processes in those clouds and their interactions with aerosols using a large-eddy simulation (LES) framework. Cloud mass becomes much lower in the presence of ice processes and the Wegener–Bergeron–Findeisen (WBF) mechanism in the mixed-phase clouds compared to that in warm clouds. This is because while the WBF mechanism enhances the evaporation of droplets, the low concentration of aerosols acting as ice-nucleating particles (INPs) and cloud ice number concentration (CINC) prevent the efficient deposition of water vapor. Note that the INP concentration in this study is based on the observed spatiotemporal variability of aerosols. This results in the lower CINC compared to that with empirical dependence of the INP concentrations on temperature in a previous study. In the mixed-phase clouds, the increasing concentration of aerosols that act as cloud condensation nuclei (CCN) decreases cloud mass by increasing the evaporation of droplets through the WBF mechanism and decreasing the intensity of updrafts. In contrast to this, in the warm clouds, the absence of the WBF mechanism makes the increase in the evaporation of droplets inefficient, eventually enabling cloud mass to increase with the increasing concentration of aerosols acting as CCN. Here, the results show that when there is an increasing concentration of aerosols that act as INPs, the deposition of water vapor is more efficient than when there is the increasing concentration of aerosols acting as CCN, which in turn enables cloud mass to increase in the mixed-phase clouds.

Influences of Entrainment-Mixing Parameterization on Numerical Simulations of Cumulus and Stratocumulus Clouds

Different entrainment-mixing processes can occur in clouds; however, a homogeneous mixing mechanism is often implicitly assumed in most commonly used microphysics schemes. Here, we first present a new entrainment-mixing parameterization that uses the grid-mean relative humidity without requiring the relative humidity of the entrained air. Second, the parameterization is implemented in a microphysics scheme in a large eddy simulation model. Third, sensitivity experiments are conducted to compare the new parameterization with the default homogeneous entrainment-mixing parameterization. The results indicate that the new entrainment-mixing parameterization has a larger impact on the number concentration, volume-mean radius, and cloud optical depth in the stratocumulus case than in the cumulus case. This is because inhomogeneous and homogeneous mixing mechanisms dominate in the stratocumulus and cumulus cases, respectively, which is mainly due to the larger turbulence dissipation rate in the cumulus case. Because stratocumulus clouds break up during the dissipation stage to form cumulus clouds, the effects of this new entrainment-mixing parameterization during the stratocumulus dissipation stage are between those during the stratocumulus mature stage and the cumulus case. A large aerosol concentration can enhance the effects of this new entrainment-mixing parameterization by decreasing the cloud droplet size and evaporation time scale. This study sheds new light on the improvement of entrainment-mixing parameterizations in models.

Cloud species classification from video recordings

Large data bank of images has been accumulated during atmospheric cloudinessground-based observations from 2017 to 2020 near Fryazino city, Moscow Region. The problemof obtained images classification into several types is considered. The types are clear sky (noclouds); cumulus cloudiness of various extent (humilis, mediocris, congestus); very powerfulclouds such as cumulonimbus or nimbostratus; stratus cloud cover; stratocumulus clouds; lightand high-positioned clouds (altocumulus, cirrus, cirrostratus and cirrocumulus). A qualitativeanalysis of the key features of gray, blue, green and red level co-occurrence matrices for variouspixel distances and directions (angles) is performed to solve the problem. An image classification algorithm based on these and other key features retrieved during image preprocessingis developed. The quality evaluation is performed. The developed software tool is currentlysuccessfully used for atmospheric radiometry problems support.

Evaluation of satellite retrievals of liquid clouds from the GOES-13 imager and MODIS over the midlatitude North Atlantic during the NAAMES campaign

Satellite retrievals of cloud droplet effective radius (re) and optical depth (τ) from the Thirteenth Geostationary Operational Environmental Satellite (GOES-13) and the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua and Terra, based on the Clouds and the Earth's Radiant Energy System (CERES) project algorithms, are evaluated with airborne data collected over the midlatitude boundary layer during the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES). The airborne dataset comprises in situ re from the Cloud Droplet Probe (CDP) and remotely sensed re and τ from the airborne Research Scanning Polarimeter (RSP). GOES-13 and MODIS (Aqua and Terra) re values are systematically greater than those from the CDP and RSP by at least 4.8 (GOES-13) and 1.7 µm (MODIS) despite relatively high linear correlation coefficients (r=0.52–0.68). In contrast, the satellite τ underestimates its RSP counterpart by −3.0, with r=0.76–0.77. Overall, MODIS yields better agreement with airborne data than GOES-13, with biases consistent with those reported for subtropical stratocumulus clouds. While the negative bias in satellite τ is mostly due to the retrievals having been collected in highly heterogeneous cloud scenes, the causes for the positive bias in satellite re, especially for GOES-13, are more complex. Although the high viewing zenith angle (∼65∘) and coarser pixel resolution for GOES-13 could explain a re bias of at least 0.7 µm, the higher GOES-13 re bias relative to that from MODIS is likely rooted in other factors. In this regard, a near-monotonic increase was also observed in GOES-13 re up to 1.0 µm with the satellite scattering angle (Θ) over the angular range 116–165∘; that is, re increases toward the backscattering direction. Understanding the variations of re with Θ will require the combined use of theoretical computations along with intercomparisons of satellite retrievals derived from sensors with dissimilar viewing geometry.

Turbulence in The Marine Boundary Layer and Air Motions Below Stratocumulus Clouds at the ARM Eastern North Atlantic Site

Marine stratocumulus clouds are intimately coupled to the turbulence in the boundary layer and drizzle is known to be ubiquitous within them. Six years of data collected at the Atmospheric Radiation Measurement (ARM)’s Eastern North Atlantic site are utilized to characterize turbulence in the marine boundary layer and air motions below stratocumulus clouds. Profiles of variance of vertical velocity binned by wind direction (wdir) yielded that the boundary layer measurements are affected by the island when the wdir is between 90° and 310° (measured clockwise from North where air is coming from). Data collected during the marine conditions (wdir<90 or wdir>310) showed that the variance of vertical velocity was higher during the winter months than during the summer months due to higher cloudiness, wind speeds, and surface fluxes. During marine conditions the variance of vertical velocity and cloud fraction exhibited a distinct diurnal cycle with higher values during the nighttime than during the daytime. Detailed analysis of 32 cases of drizzling marine stratocumulus clouds showed that for a similar amount of radiative cooling at the cloud top, within the sub-cloud layer 1) drizzle increasingly falls within downdrafts with increasing rain rates, 2) the strength of the downdrafts increases with increasing rain rates, and 3) the correlation between vertical air motion and rain rate is highest in the middle of the sub-cloud layer. The results presented herein have implications for climatological and model evaluation studies conducted at the ENA site, along with efforts of accurately representing drizzle-turbulence interactions in a range of atmospheric models.

Parameterising cloud base updraft velocity of marine stratocumuli

The number of cloud droplets formed at the cloud base depends both on the properties of aerosol particles and the updraft velocity of an air parcel at the cloud base. As the spatial scale of updrafts is too small to be resolved in global atmospheric models, the updraft velocity is commonly parameterised based on the available turbulent kinetic energy. Here we present alternative methods through parameterising updraft velocity based on high-resolution large eddy simulation (LES) runs in the case of marine stratocumulus clouds. First we use our simulations to assess the accuracy of a simple linear parametrisation where the updraft velocity depends only on cloud top radiative cooling. In addition, we present two different machine learning methods (Gaussian process emulation and random forest) that account for different boundary layer conditions and cloud properties. We conclude that both machine learning parameterisations reproduce the LES-based updraft velocities at about the same accuracy, while the simple approach employing radiative cooling only produce on average lower coefficient of determination and higher root mean square error values. Finally, we apply these machine learning methods to find the key parameters affecting cloud base updraft velocities.